Submission¶

Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace

In [1]:
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px
import pandas as pd
import numpy as np

init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
In [2]:
#load data
df = px.data.gapminder()
df.head()
Out[2]:
country continent year lifeExp pop gdpPercap iso_alpha iso_num
0 Afghanistan Asia 1952 28.801 8425333 779.445314 AFG 4
1 Afghanistan Asia 1957 30.332 9240934 820.853030 AFG 4
2 Afghanistan Asia 1962 31.997 10267083 853.100710 AFG 4
3 Afghanistan Asia 1967 34.020 11537966 836.197138 AFG 4
4 Afghanistan Asia 1972 36.088 13079460 739.981106 AFG 4

Question 1:¶

Recreate the barplot below that shows the population of different continents for the year 2007.

Hints:

  • Extract the 2007 year data from the dataframe. You have to process the data accordingly
  • use plotly bar
  • Add different colors for different continents
  • Sort the order of the continent for the visualisation. Use axis layout setting
  • Add text to each bar that represents the population
In [3]:
df1   = df[df.year == 2007]                               # Extract 2007 data
df2   = pd.DataFrame(df1.groupby(by=df.continent).sum())  # Sum the population per continent
dfnew = pd.DataFrame(df2['pop'])

fig = px.bar(dfnew,                                       # Use plotly bar
             title='Population per continent (2007)',                      
             x='pop', 
             y=dfnew.index, 
             orientation='h', 
             color=dfnew.index)                           # Add different colors for different continents
fig.show()

Question 2:¶

Sort the order of the continent for the visualisation

Hint: Use axis layout setting

In [4]:
fig.update_yaxes(categoryorder='total ascending')   # Sort order of continents
fig.show()

Question 3:¶

Add text to each bar that represents the population

In [5]:
fig = px.bar(dfnew,                                     
             title='Population per continent (2007)',                      
             x='pop', 
             y=dfnew.index, 
             orientation='h', 
             color=dfnew.index,
             text_auto='.2s')                           # Add text to each bar that represents the population
fig.update_traces(textposition='outside')
fig.show()

Question 4:¶

Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years

In [6]:
fig = px.bar(df, x="pop", y="continent", color="continent", 
             animation_frame="year", animation_group="country", range_x=[0,4*10**9])
fig.update_layout(barmode='stack')
fig.update_traces(marker_line_width=0)
fig.update_yaxes(categoryorder='total ascending')
fig.show()

Question 5:¶

Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years

In [7]:
fig = px.bar(df, x="pop", y="country", color="country", 
             animation_frame="year", animation_group="country", 
             range_x=[0, 1.5*10**9])
fig.update_layout(barmode='stack')
fig.update_traces(marker_line_width=0)
fig.update_yaxes(categoryorder='total ascending')
fig.show()

Question 6:¶

Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation

In [8]:
fig.update_layout(height=1000)
fig.show()

Question 7:¶

Show only the top 10 countries in the animation

Hint: Use the axis limit to set this.

In [9]:
fig.update_yaxes(range=(len(df.country.unique())-10.5, 
                        len(df.country.unique())-0.5))
fig.update_layout(height=600)
fig.show()
In [ ]: